Despite the latest advances in imaging technology, cancer is still often diagnosed after metastasis has occurred. Needless deaths from cancer occur as a consequence of detection after metastasis. Therefore, detection of cancer prior to metastasis is an urgent social priority.
An approach for such early detection is molecular testing. Molecular testing, in which molecular markers are used to detect cancer, is emerging as an attractive method for cancer screening due to its ability to allow physicians to detect cancer at the earliest stage by analysis of a single drop of bodily fluid or a small stool sample.
DNA mutation and aberrant methylation of genes are among the most common DNA alteration events leading to the development of cancer. For example, mutations in the gene p53 occur in approximately 50-60% of all cancers. Aberrant methylation of genes is found in many types of cancers. Hence, DNA mutation and methylation serve as cancer indicators or markers and thus if identified, can be used to diagnose cancer. Because of this, efforts have been made to develop DNA-based assays to screen cancer. For example, fecal DNA testing based on mutation analysis of several genes was developed for colorectal cancer (CRC) screening. Similarly, fecal DNA testing based on methylation analysis has also been used to screen for colorectal cancer.
Despite use as a cancer indicator, mutation analysis remains a technical challenge when applied to screening. This is due to two reasons. First, detection of mutations in clinical samples requires methods that are highly sensitive. Since clinical specimens comprise a minority of mutated sequences (often less than 1%) in a vast excess of wild-type sequences, only highly sensitive assays can be used. Furthermore, cancer can result from different pathways involving the accumulation of mutations in different genes and thus no single mutation event can serve as a reliable indicator of cancer. As a consequence, a panel or collection of genes must be used to detect cancer. For example, fecal DNA testing utilizes mutations in k-ras, p53, APC, and BAT26 as markers to detect colorectal cancer. Moreover, mutations in a gene often occur in different bases. For example, the APC mutations can occur anywhere within its first 1600 codons. Thus, a clinical test must be able to survey the mutation status of a large number of markers in a vast excess population of wild-type DNA.
Second, cancer screening must be cost-effective, since this factor eventually determines the extent to which such method is used in health care intervention. Fecal occult testing is a good example. Fecal occult testing is not particularly sensitive, but is more cost-effective than other methods. As a result, fecal occult testing is the method recommended by the U.S. Preventive Services Task Force for CRC screening. It is virtually impossible for medical policy makers and/or insurance companies to embrace a screening test that is not cost-effective. Thus, a good clinical screening test must be cost-effective in addition to providing a reasonable degree of sensitivity.
A number of methods have been employed to detect mutations. In general, these methods can be classified into two groups. In one set of methods, polymerase chain reaction (PCR) is a component of the detection system. These methods rely on the selective amplification of mutant alleles and allow the sensitive detection of mutant alleles in a great excess population of wild-type alleles. Allele-Specific-Amplification (ASA) and Mutant Enriched PCR (ME-PCR) are two widely used methods for this application, both of which can detect mutant DNA in an excess of wild-type DNA having a population 100,000 times greater than that of the mutant DNA. However, these methods enrich mutant DNA by PCR and each PCR reaction generally detects one mutation. As previously noted, a large panel of mutations must be utilized to attain high screening sensitivity. Therefore, a number of PCR reactions would be needed if this set of methods is used for cancer screening, thereby increasing the screening cost. Hence, assays employing this set of methods may not be cost-effective, and thus would not be suitable for clinical screening.
In the second set of methods, mutations are analyzed after the target sequence has been amplified by PCR. Mutations can then be analyzed using technologies such as sequencing, DHPLC, DNA microarray, DGGE, and SSCP. Unlike the first set of methods, the second set of methods can survey the mutations within a long sequence span. However, these methods are not sufficiently sensitive to detect mutations in a large background of wild-type DNA. As a result, although this group of methods has been routinely used to detect mutations in DNA derived from dissected tumor samples where the abundance of mutant DNA is relatively high, the poor sensitivity of this set of methods has generally impeded their use to detect mutations in DNA derived from clinical specimens such as bodily fluids and stool, where the abundance of mutant DNA is low. Hence, the second set of methods is also not suitable for clinical screening because of their poor sensitivity.
Recently, a PCR/ligase detection reaction (LDR) method for mutation analysis has been proposed, which combines polymerase chain reaction/ligase detection reaction with DNA microarray. A feature of this method is that it can survey the mutation status of a number of markers and it has been used to detect mutations in DNA derived from clinical specimens. However, this method has limitations. Although high sensitivity was reported with a single mutation system, it remains a challenge to attain a high sensitivity when PCR/LDR is used to survey hundreds of mutations. This is because LDR may not be equally sensitive for all sequences, as it relies on the ability of ligase to distinguish different sequences. More importantly, amplification by PCR varies greatly from sequence to sequence and thus some mutations may not be detectable in a multiplexed setting. Thus, it is a challenge to detect mutations if their sequences are poorly amplified in multiplexed PCR.
Clearly, there is an urgent need in the art for analysis of the status of a large panel of DNA mutation markers in a large background of wild-type DNA in a sensitive and cost-effective manner.
As previously noted, aberrant methylation of genes is a DNA alteration event that frequently leads to cancer. Methylation refers to the biochemical addition of a methyl group (—CH3) to a biological molecule. Aberrant methylation of CpG dinucleotides in the 5′ regulatory region of genes is a common event leading to gene silence. As a result of CpG island hypermethylation, chromatin structure in the promoter can be altered, thereby preventing normal interaction with the transcriptional machinery. It is now clear that aberrant methylation is a widespread phenomenon in cancer. If this occurs in genes critical to growth inhibition, the resulting silencing of transcription could promote tumor progression. Thus, like mutation, promoter CpG island hypermethylation is a common mechanism for transcriptional inactivation of tumor suppressor genes. There has been considerable interest in methylation analysis, as methylation analysis can not only yield insights into cancer, but this analysis may also lead to the discovery of therapeutic and diagnostic biomarkers. Recently, monitoring global changes in DNA methylation has been applied to molecular classification of cancer. More recently, it was found that methylation was associated with response to cancer treatment. Therefore, methylation markers can also be used to classify and predict types and stages of cancer, cancer therapeutic outcomes, and survival.
Methylation analysis is a key to the characterization of DNA methylation. Despite its importance, however, methylation analysis remains a technical challenge, especially when biospecimens are analyzed. This is due to two issues. The first one is sensitivity. The methods for analysis of clinical samples must be sensitive, as biospecimens are heterogeneous and often comprise minority methylated sequences in an excess of unmethylated sequences. For example, tissue specimens such as paraffin-embedded samples may contain as little as 1% of altered DNA and their abundance is even lower in other clinical biospecimens such as bodily fluids, blood, urine, and stool. Thus, only highly sensitive assays can reveal methylation in a vast excess of unmethylated DNA.
The second issue relating to methylation analysis being a technical challenge is multiplexing capability. Cancer results from different pathways involving accumulation of methylation in many genes and no single methylation event can provide an accurate indicator for cancer analysis. As a result, a large panel of genes must be profiled to characterize the association of methylation with cancer. Hence, technologies for methylation analysis should also have high-order multiplexing capability. In addition, the number of altered DNA molecules is limited in clinical specimens. This is a problem especially for methylation analysis as only 10-20% of the DNA molecules can be recovered after bisulfite treatment. Hence, multiplexing capability is essential to methylation analysis as there are insufficient amounts of altered DNA molecules in clinical biospecimens to allow the analysis of one gene at a time.
Methylation analysis can profile methylation globally, identify methylation patterns at a cluster of CpG sites or genes, and determine methylation levels at individual CpG sites. Methylation-restriction enzyme digestion is a good method for methylation analysis, but most of the currently used methods are based on bisulfite treatment which can convert cytosine to uracil whereas the methylated cytosine residues are unaltered. The treated DNA is then amplified by PCR with specific primers to yield fragments in which all uracil residues are converted to thymine. As a result of the differences in the sequences of methylated and unmethylated DNA created by bisulfite treatment, the methylation status at a CpG site can be determined using a conventional mutation analysis method. Thus, the methylation status of a CpG site can be determined by a mutation analysis method after bisulfite treatment.
Current bisulfite-based methods for methylation analysis can be classified into three approaches. The first approach is bisulfite-based sequencing that can map methylated cytosine residues within a gene promoter. Its advantage is that it identifies every methylated cytosine within a gene promoter, but its weakness is its poor sensitivity and lack of multiplexing capability. The second approach combines bisulfite-PCR with a DNA microarray to distinguish methylated from unmethylated alleles within the targeted sequences. This approach allows parallel evaluation of the methylation status at numerous CpG sites within many genes of interest. However, it is not sufficiently sensitive to detect minority methylation DNA in a large background of unmethylated DNA. The third approach is methylation-specific PCR (MSP) and its many variations such as MethyLight. This approach is highly sensitive and can detect one methylated allele in 10,000 copies of unmethylated alleles. In addition, real time-based MSP can quantify the abundance of methylated DNA. However, this approach generally analyzes the methylation status one gene at a time and has limited multiplexing capability. In addition, this approach surveys the methylation status only at a few closely neighboring CpG sites. Clearly, these methods either are not sufficiently sensitive, or do not have multiplexing capability, or both.
More recently, two ligation-based approaches have been developed for methylation analysis. In the first approach, a PCR/LDR method is utilized for methylation analysis. This method is similar to the previously noted technology developed for mutation analysis. Briefly, it first utilizes multiplexed PCR to amplify multiple target DNA sequences, followed by ligation reactions. The ligation products are then analyzed using a microarray to determine the methylation status at each target CpG site. In the second approach, a genotyping system is applied to methylation detection. Unlike the first approach, this second approach utilizes ligation to produce both methylated and unmethylated alleles, which is then followed by multiplexed PCR to amplify the sequences containing each target CpG site. The methylation status at each CpG site is analyzed using a microarray. Ligation-based methods can survey the methylation status at numerous CpG sites of many genes of interest. But their detection sensitivity is still relatively poor and thus they are generally used for analysis of the samples containing 10% or more of altered DNA. Such sensitivity is certainly not sufficiently high to detect low abundance methylated DNA in many types of clinical biospecimens, especially in the samples where the abundance of altered DNA can be less than 1%.
Clearly, there is an urgent need in the art for analysis of the methylation status of a large number of CpG sites of many genes of interest in a large background of wild-type DNA in a sensitive and cost-effective manner.